Computational systems pathology spatial analysis platform for in situ or in vitro multi-parameter cellular and subcellular imaging data

A computerized system for generating a representation of spatially informed heterocellular communication from multi-parameter cellular and subcellular imaging data obtained from a number of tissue samples from a number of patients or a number of multicellular in vitro models, comprising:

• a processing apparatus, wherein the processing apparatus includes:
• a spatial heterogeneity quantification component configured for generating a quantification of a spatial heterogeneity among cells of certain varying predetermined phenotypes in the multi-parameter cellular and subcellular imaging data, including performing cell phenotyping on the multi-parameter cellular and subcellular imaging data to identify the certain varying predetermined phenotypes;
• a microdomain identification component configured for identifying a plurality of microdomains for the number of tissue samples based on the quantification, each microdomain being associated with one of the tissue samples;
• and
• a communication network component configured for constructing a communications graph for a selected one of the microdomains, wherein each of the phenotypes is a node in the communications graph, and wherein an edge between each pair of the phenotypes in the communications graph is indicative of an influence of one phenotype in the pair on a presence of the other phenotype in the pair, wherein each phenotype in the communications graph is represented by a data vector obtained from the multi-parameter cellular and subcellular imaging data, and wherein communication network component is configured for:
• for each pair of the phenotypes, establishing a numerical relationship between the phenotypes in the pair by determining a strength of association or influence value between the data vectors of the phenotypes in the pair, and establishing a directionality for each of the numerical relationships, wherein the edge between each pair of the phenotypes is indicative of the numerical relationship between the phenotypes in the pair and the directionality of the numerical relationship between the phenotypes in the pair.

A method of creating a personalized medicine strategy for a specific patient, wherein the specific patient is one of a number of patients, and wherein the number of patients has associated therewith multi-parameter cellular and subcellular imaging data obtained from a number of tissue samples from the number of patients, the method comprising:

• identifying a plurality of microdomains in one of the tissue samples that is associated with the specific patient, wherein the plurality of microdomains are based on the multi-parameter cellular and subcellular imaging data and wherein each microdomain includes a plurality of phenotypes;
• generating a heterocellular communication graph for each of the microdomains, wherein each heterocellular communication graph comprises a representation of spatially informed heterocellular communication for the microdomain, wherein each of the phenotypes of the microdomain is a node in the communication graph, and wherein an edge between each pair of the phenotypes in the communications graph is indicative of an influence of one phenotype in the pair on a presence of the other phenotype in the pair, wherein each phenotype in the communications graph is represented by a data vector obtained from the multi-parameter cellular and subcellular imaging data, and wherein the method includes, for each pair of the phenotypes, establishing a numerical relationship between the phenotypes in the pair by determining a strength of association or influence value between the data vectors of the phenotypes in the pair, and establishing a directionality for each of the numerical relationships, wherein the edge between each pair of the phenotypes is indicative of the numerical relationship between the phenotypes in the pair and the directionality of the numerical relationship between the phenotypes in the pair;
• generating a quantification of an interdependence of the microdomains in space and time based on the heterocellular communication graphs;
• and
• designing the medicine strategy for the specific patient based on the quantification.

A method of representing a time evolution of disease progression in a specific patient, wherein the specific patient is one of a number of patients, and wherein the number of patients has associated therewith multi-parameter cellular and subcellular imaging data obtained from a number of tissue samples from the number of patients, the method comprising:

• generating a geometrical representation of a disease landscape for the specific patient, wherein the geometrical representation includes a plurality of points, wherein each point on the geometrical representation:
• (i) describes a disease status of the specific patient at a particular time and is based on a particular one of the tissue samples that is associated the selected patient, (ii) is based on a microdomain in the particular one of the tissue samples that is based on the multi-parameter cellular and subcellular imaging data, wherein the microdomain includes a plurality of phenotypes, and (iii) includes a heterocellular communication graph for the microdomain that comprises a representation of spatially informed heterocellular communication for the microdomain, wherein each of the phenotypes of the microdomain is a node in the communication graph, and wherein an edge between each pair of the phenotypes in the communications graph is indicative of an influence of one phenotype in the pair on a presence of the other phenotype in the pair, wherein each phenotype in the communications graph is represented by a data vector obtained from the multi-parameter cellular and subcellular imaging data, and wherein the method includes, for each pair of the phenotypes, establishing a numerical relationship between the phenotypes in the pair by determining a strength of association or influence value between the data vectors of the phenotypes in the pair, and establishing a directionality for each of the numerical relationships, wherein the edge between each pair of the phenotypes is indicative of the numerical relationship between the phenotypes in the pair and the directionality of the numerical relationship between the phenotypes in the pair.